Extropic
Research Scientist - Machine Learning
$150K–$250K
Boston · On-site · Full-time · Posted Apr 22, 2026
- Visa sponsorship
- Employment offers are conditioned on authorization to receive controlled items subject to U.S. export control laws and regulations, including the EAR.
About the job
Develops probabilistic machine learning theory and models using Extropic’s thermodynamic computing paradigm, from research and scaling experiments through production deployment.
What you'll do
- Derive theories and learning rules for probabilistic models, including energy-based and diffusion models.
- Build experimentation infrastructure; implement, evaluate, and optimize model architectures, training algorithms, and benchmarks.
- Publish research, contribute to open source, communicate insights to hardware teams, and develop production models using customer data.
What they ask for
- Experience with scientific Python and at least one deep learning framework (PyTorch, JAX, TensorFlow, Keras).
- Strong foundations in probability and linear algebra, and familiarity with deep learning theory and literature, including over-parameterization theory and scaling laws.
- Publications in top ML conferences (NeurIPS, ICML, ICLR, CVPR).
- Experience training high-performance models and deploying models, including familiarity with the stated infrastructure.
Nice to have
- Experience with probabilistic graphical models, energy-based or diffusion models, numerical methods in diffeq solvers, message passing, or graph neural networks.
- Theoretical background in information geometry or random matrix theory, or computational Bayesian methods including MCMC and variational inference.
Pay
$150K – $250K (base salary)
Tools
Python, PyTorch, JAX, TensorFlow, Keras, Slurm, Ray, Weights & Biases
AI focus
Research and develop probabilistic ML theory, training methods, scaling experiments, and performant production models, including energy-based and diffusion models.
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